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Innovative Energy & Research | ISSN: 2576-1463 | Volume 7
Renewable Energy and Resources
Energy Materials and Fuel Cell Research
2
nd
International Conference on
&
August 27-28, 2018 | Boston, USA
Diagnosis of membrane chemical degradation for a health management system of polymer electrolyte
fuel cells
Derek Low
Loughborough University, United Kingdom
D
ue to increasing global energy consumption and carbon emissions from using fossil fuels as a primary energy source, low
carbon electricity generation is increasingly important as society is shifting towards a more sustainable and electrified
future to reduce carbon emissions and its effect on the environment. Polymer electrolyte fuel cells are a promising technology
which can provide efficient electricity generation with zero carbon emissions. However, their reliability and durability are one
of the main challenges to widespread commercialization. Improving these aspects is necessary for achieving lifetime targets.
Diagnostics and prognostics are key components in a strategy to improve reliability and durability. The challenge of current
methods to accurately model degradation and predict lifetime is highly complex due to the multiple interrelated degradation
mechanisms.This research presents a diagnostic fuzzy inference system approach for healthmanagement of polymer electrolyte
fuel cells. The investigation focused on the diagnosis of membrane chemical degradation as this was identified as a top priority.
The fuzzy inference system facilitates the connection between operating conditions and subsequent degradation modes.
An inference calculation is performed based on rules developed from fuel cell degradation knowledge without the need for
complex mathematical models. This fuzzy diagnostic approach enables enhanced health management allowing for proactive
decision-making thereby improving fuel cell reliability and durability. This increases fuel cell availability and lifetime resulting
in a more valuable product. Fuel cell testing was conducted under various operating conditions known to cause membrane
chemical degradation. Results support the proposed rules for the diagnostic fuzzy inference system.
Biography
Derek has completed his BEng degree in Renewable Energy and Sustainable Technologies from Glyndwr University. He has also completed his MSc degree in
Renewable Energy Systems from Loughborough University within the Centre for Renewable Energy Systems Technology (CREST). He is currently in the third year
of a four year PhD with integrated studies. His PhD research is part of a wider project in the Centre for Doctoral Training in Fuel Cells and Their Fuels which in-
cludes four other partner universities including the University of Birmingham, University College London, Imperial College London and the University of Nottingham.
D.Low@lboro.ac.ukDerek Low, Innov Ener Res 2018, Volume 7
DOI: 10.4172/2576-1463-C2-006